Complementary metal-oxide-semiconductor (CMOS) image sensors have in recent years been widely employed in image sensing applications such as digital cameras, video camcorders, scanners and the like. CMOS image sensors sense light by taking advantage of photoelectric effect. Photoelectric effect occurs when photons interact with crystallized silicon to energize and move electrons from the valence band into the conduction band, where the electrons can be harnessed, creating electric current at a voltage related to the bandgap energy. A conventional CMOS image sensor typically contains a focal plane array of light-sensing elements, referred to as picture elements or pixels, and readout circuitry that outputs signals indicative of the light sensed by the pixels. Each light-sensing element includes a photosensor, which may be a photodiode, a photoconductor, a photogate or the like. When a photosensor is exposed to light, it records the intensity or brightness of the light that falls on it by accumulating an electric charge that is proportional to the brightness of the light due to the photoelectric effect. The brightness recorded by the photosensor in the form of accumulated electric charge is then sampled, amplified, converted into and stored as a representative digital signal that can be used to recreate the image on a screen or on a printed paper.
In operation, the photosensor in each pixel of a CMOS image sensor accumulates photo-generated charge in a specified portion of the substrate. The photosensor capacitance is discharged through a constant integration of time at a rate that is approximately proportional to the illumination of the incident light. The charge rate of the photosensor capacitance is used to convert the optical signal to an electrical signal, as is known in the art. A readout circuit for pixel sampling is coupled to the photosensor, and includes at least a source follower transistor and a row select transistor for coupling the source follower transistor to a column output line. Charge that is generated by the photosensor is transferred to a sensing region, typically a floating diffusion node, connected to the gate of the source follower transistor. For each pixel, the CMOS image sensor may also include a device, such as a transistor, for transferring charge from the photosensor to the floating diffusion node, and another device, also typically a transistor, for resetting the storage region to a predetermined charge level prior to charge transfer.
During sampling, values of the pixels are sampled typically a row of pixels at a time, known as row-wise sampling, using either interlaced or progressive scans. However, a consequence of row-wise sampling is that the pixel values from a single row are susceptible to and contain both correlated noise and non-correlated noise. For example, noise on power supply and common bias lines are sources that will result in correlated noise. When the correlated row noise component changes from row to row, an undesirable effect is likely to result in the form of horizontal stripes in the recreated image. Since the human eye is sensitive to structural noise, such as row-wise noise, it is important to minimize such noise in an image sensor.
One approach to reduce row-wise noise is to first estimate the correlated noise component and then subtract it from the active pixels on the same row in the digital domain. The correlated noise can be estimated, for instance, by averaging values from a set of dark reference pixels on the same row. In general, a dark reference pixel is structurally the same as an active pixel and could be, for example, an active pixel with an optical shield (e.g., black color filter array) or an active pixel with the photosensor tied to the power supply. Dark reference pixels are utilized not to sense light but to sense noise that the rows of active pixels are exposed to.
However, such approach will convert non-correlated noise from the dark reference pixels to row-wise noise. This is so because the averaging of values from the dark reference pixels leads to an estimator noise, σPIX/N0.5, where σPIX is the standard deviation for the pixel-wise noise (non-correlated) and N is the number of averaged pixel values. As the number of averaged dark reference pixels is increased in order to reduce the estimator noise, the overhead upon processing a signal row is increased accordingly. This will in turn require an increase in the conversion rate for the analog readout channel, including amplifier and analog-to-digital converter, in order to meet a certain frame rate. Nevertheless, that may not be desirable or feasible for reasons such as limited die size and the need to minimize power consumption, just to name a few. There is, therefore, a need to suppress row-wise noise in the analog domain before analog-to-digital conversion in order to minimize overhead in per-row processing of pixel values.